The primary school stage is the key stage for students to form good habits and lay a good learning foundation, especially in primary schools, Chinese classes account for the largest proportion of all courses, the focus of learning began to shift to understanding and mastering. Through scientific methods, teachers can effectively improve the concentration of Chinese learning of primary school students in order to improve their interest and overall level,to have a profound impact on the future study and life of primary school students. This paper analyzes the importance and strategies of teachers' attention training in the middle Chinese classroom of primary school.
With the advent of the era of globalized economy, more attention should be paid to the training mode of comprehensive English literacy in colleges and universities in teaching. Therefore, how to cultivate and improve students' higher-level teaching methods in the context of ecolinguistics, so as to improve the quality of English teaching, is the current focus of English teaching in colleges and universities. By summarizing the basic concepts of ecolinguistics, this paper studies effective measures to improve the quality of linguistics teaching in colleges and universities, and comprehensively improves the quality and efficiency of English language teaching in colleges and universities under the background of ecolinguistics.
In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.
Lately, there is a progressive assimilation of sustainable and green development principles into the collective conscience of individuals. Companies have received considerable attention from all sectors of life when it comes to the environment, society and governance (ESG). This study uses a bidirectional fixed effects model to investigate the influence and the mechanism of green innovation on company ESG information, using a research sample composed of data from the A-share listed companies in China spanning the period from 2011 to 2021. The findings indicated that green innovation exerted a substantial positive influence on ESG information disclosure, and the effect was more substantial, especially in mature and declining companies. Financing constraints and analysts’ attention played a mediating role between green innovation and ESG information disclosure. The results of heterogeneity analysis showed that green innovation played a more significant role in promoting ESG information disclosure among state-owned companies, large-scale companies, manufacturing companies and heavy pollution companies. Furthermore, implementing green development policies had facilitated the reinforcement of the promotion impact of ESG information disclosure through green innovation. Additionally, the instrumental variable method was employed to conduct a robustness test. This study enhances the understanding of the theoretical framework about green innovation and the disclosure of ESG information, and offers valuable insights for advancing the sustainable development of companies.
A large number of consumers in Malaysia are resistant towards new technology and prefer instead the tried and tested way of doing things. It is worth examining if local consumers are in fact ready to digitize and accept technology in their day-to-day dealings. A behavioral study was developed to gauge the digital maturity and tech preparedness of Malaysian consumers with regards to loyalty and how this will reflect an individual’s predisposition in his or her ability and eventual use of a new technology. This study latched on to the concept of tech preparedness. A conceptual framework was developed after reviewing existing scholarly literature. This was then tested through a survey using a convenience sample from 383 SME consumers in the country. This study also looked at the difference in tech preparedness among gender, age and level of education. During the Investigation regarding Industry 4.0, it was noticed that there are few studies dealing with this segment of companies in Malaysia. In addition in team of this research about customer perspective the amount of studies become more less and also because of the Shortage of the necessary skills, talents and knowledge for adopting Industry 4.0, the number Malaysian company ready to move or already move to industry 4.0 is quit few and it seems to cause less experience using new technology among Malaysian customers.
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